ToolUniverse is a collection of tools, interfaces, and supporting components for building AI systems that perform scientific work. It is for developers creating AI scientist agents that use APIs, databases, machine-learning tools, and domain-specific utilities. The catalogue includes skills, commands, an MCP server, an agent, and a hook for working with the ecosystem.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mims-harvard/ToolUniverse --skill tooluniverse-comparative-genomicsgit clone --depth 1 https://github.com/mims-harvard/ToolUniverseWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mims-harvard/tooluniverse/tooluniverse-comparative-genomics)<a href="https://agentmods.dev/skills/mims-harvard/tooluniverse/tooluniverse-comparative-genomics"><img src="https://agentmods.dev/badge/skills/mims-harvard/tooluniverse/tooluniverse-comparative-genomics/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mims-harvard/tooluniverse/tooluniverse-comparative-genomics"><img src="https://agentmods.dev/badge/skills/mims-harvard/tooluniverse/tooluniverse-comparative-genomics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00090 | $0.03469 |
| Opus 5 | $0.00045 | $0.01734 |
| Sonnet 5 | $0.00018 | $0.00694 |
| Haiku 4.5 | $0.00009 | $0.00347 |
Grade A, and why
tooluniverse-comparative-genomics scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Comparative Genomics & Ortholog Analysis
Cross-species gene comparison, ortholog identification, sequence retrieval, and functional conservation analysis integrating Ensembl Compara, NCBI, UniProt, OLS, Monarch, and OpenTargets.
LOOK UP, DON'T GUESS
When uncertain about any scientific fact, SEARCH databases first (PubMed, UniProt, ChEMBL, ClinVar, etc.) rather than reasoning from memory. A database-verified answer is always more reliable than a guess.
COMPUTE, DON'T DESCRIBE
When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.
When to Use This Skill
Triggers:
- "Find the mouse ortholog of [human gene]"
- "Compare [gene] across species"
- "Is [gene] conserved in [organism]?"
- "What are the orthologs of [gene]?"
- "Cross-species comparison of [gene/protein]"
- "Evolutionary conservation of [gene]"
- "Compare GO annotations between human and mouse [gene]"
Use Cases:
- Ortholog Discovery: Find equivalent genes in other species for a human gene
- Conservation Analysis: Assess how conserved a gene is across evolutionary distance
- Functional Comparison: Compare GO terms, domains, and annotations across orthologs
- Model Organism Selection: Determine which model organism best recapitulates human gene function
- Gene Tree Analysis: Visualize evolutionary history of a gene family
- Cross-Species Phenotype Bridging: Link human disease phenotypes to model organism phenotypes via orthologs
Conservation Reasoning Framework
Understanding conservation requires distinguishing between types of evolutionary patterns and what they imply about function.
High conservation signals functional constraint. When a gene is maintained as a 1:1 ortholog from yeast to humans, purifying selection has prevented sequence divergence — the gene's function is essential and cannot be easily altered. Highly conserved positions within a protein sequence (high PhastCons scores > 0.8, or GERP RS > 4) are under strong constraint; mutations at these positions are disproportionately pathogenic. For non-coding regions, conservation in mammals at PhastCons > 0.5 suggests a candidate regulatory element.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 182 lines · 90 tokens per session scan A 3a0265521fed
tooluniverse-comparative-genomics is a skill published in the GitHub repository mims-harvard/ToolUniverse (1,680 stars, last pushed yesterday), licensed Apache-2.0. It adds 90 tokens to every session and 3,469 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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